Simulation and prediction of discharge coefficient of combined weir–gate structure

Author:

Aein Nima1,Najarchi Mohsen2ORCID,Mirhosseini Hezaveh Seyyed Mohammad3,Najafizadeh Mohammad Mehdi4,Zeighami Ehsanollah3

Affiliation:

1. PhD candidate, Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran

2. Assistant Professor, Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran (corresponding author: )

3. Assistant Professor, Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran

4. Professor, Department of Mechanical Engineering, Arak Branch, Islamic Azad University, Arak, Iran

Abstract

Combined weir–gate structures are important structures for controlling the water level, measuring discharge and avoiding sediment deposition behind a weir. They can be used, for example, in irrigation channels and waste water systems. Using three-dimensional numerical software (Flow-3D) and experimental data from the literature, four combined systems of a triangular weir and a rectangular gate with different geometries were simulated. Dimensional analyses were then performed to determine the dimensionless parameters that affect the discharge coefficient of such structures. Four different intelligent system models were used to estimate the discharge coefficient and their results were compared. It was found that Flow-3D is highly capable of simulating the flow over a combined structure. Goodness of fit criteria also showed that the numerical solver estimated the water head and discharge coefficient very well. The results of all the models showed that the discharge coefficient had an inverse relation with the dimensionless parameters h/b, h/d and h/y (h being the water head over the weir, b the gate width, d the gate height and y the distance between the bottom of the weir and above the gate); the discharge coefficients were 0·3–0·9. Accuracy analyses of six intelligent system models showed that the multi-layer perceptron model was the superior model, followed by the M5P model, the regression equation, the radial basis function and the generalised regression neural network model.

Publisher

Thomas Telford Ltd.

Subject

Water Science and Technology

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